Issue #1

November 28 2013

Featured This Week

Data is meaningless unless it helps make decisions that have measurable impact. Unfortunately, many decision makers are ensnared rather than enlightened by Big Data, preventing data and insights from making it to the front lines in relevant and usable forms...In our experience, generating value from Big Data is a matter of connecting data to insights to action in a fast, repeatable way. Picture a factory...

Some say big data is all talk and no action. I couldn’t disagree more. As someone that helps companies understand and harness big data, I see new and fascinating applications every day, where people gain real benefits. I have tried to classify the application of big data into 9 categories. For me, they represent the key areas in which big data analytics are currently applied to generate the biggest value...

An Ode to Little Data
Big Data = few corporate players, big pocketbooks, big innovation...Little Data = rest of the world, little pocketbooks, little innovation: But what about the long tail? What about the rest of us? What about Little Data?

Machine Learning for Relevance and Serendipity
Careful use of well-designed machine learning systems can transform products by providing highly personalized user experiences. In this talk, I will discuss our deeply-integrated use of machine learning and natural language processing for content discovery at Prismatic.

Singing the Missing-Data Blues
I’m currently in the throes of assembling data to use in forecasts on various forms of political change in countries worldwide for 2014. This labor-intensive process is the not-so-sexy side of “data science” that practitioners like to bang on about if you ask us, but I’m not going to do that here. Instead, I’m going to talk about how hard it is to find data sets that applied forecasters of rare events in international politics can even use in the first place...

How Python became the Language of Choice for Data Science
Nowadays Python is probably the programming language of choice (besides R) for data scientists for prototyping, visualization, and running data analyses on small and medium sized data sets. And rightly so, I think, given the large number of available tools. However, it wasn’t always like this...

Neuroscientists Develop 5D Data Visualization Technique
One of the key challenges of big data is taking the enormous amounts of information and turning it into something useful that can be consumed and ingested by the human brain. This week, neuroscientists at the Florida Atlantic University (FAU) say they have developed a new type of visualization – a five dimensional colorimetric model that they say will help them visualize data across space and time.

Jobs

Adobe is looking for a Data Scientist (or Senior Data Scientist based on experience) to help build the web’s next generation of products that will allow digital marketers to maximize revenue and expand their brand presence. The position will have a good balance between research and development...

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